小编Reg*_*A A的帖子

我from object_detection.utils import label_map_util在 jupyter notebook 中执行时遇到了它。其实就是tensorflow对象检测教程notebook（自带tensorflow对象检测api）完整的错误日志：

AttributeError                            Traceback (most recent call last)
<ipython-input-7-7035655b948a> in <module>
      1 from object_detection.utils import ops as utils_ops
----> 2 from object_detection.utils import label_map_util
      3 from object_detection.utils import visualization_utils as vis_util

~\AppData\Roaming\Python\Python37\site-packages\object_detection\utils\label_map_util.py in <module>
     25 import tensorflow as tf
     26 from google.protobuf import text_format
---> 27 from object_detection.protos import string_int_label_map_pb2
     28 
     29 

~\AppData\Roaming\Python\Python37\site-packages\object_detection\protos\string_int_label_map_pb2.py in <module>
     19   syntax='proto2',
     20   serialized_options=None,
---> 21   create_key=_descriptor._internal_create_key,
     22   serialized_pb=b'\n2object_detection/protos/string_int_label_map.proto\x12\x17object_detection.protos\"\xc0\x01\n\x15StringIntLabelMapItem\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\n\n\x02id\x18\x02 \x01(\x05\x12\x14\n\x0c\x64isplay_name\x18\x03 \x01(\t\x12M\n\tkeypoints\x18\x04 \x03(\x0b\x32:.object_detection.protos.StringIntLabelMapItem.KeypointMap\x1a(\n\x0bKeypointMap\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05label\x18\x02 \x01(\t\"Q\n\x11StringIntLabelMap\x12<\n\x04item\x18\x01 \x03(\x0b\x32..object_detection.protos.StringIntLabelMapItem'
     23 ) …

我尝试遍历不同的超参数以构建最佳模型。但是在 1 次迭代（1 个模型的训练）完成后，我在第二次迭代开始时内存不足。ResourceExhaustedError: OOM when allocating tensor with shape[5877,200,200,3] and type double on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:GatherV2]

我尝试使用 ops.reset_default_graph()但它没有做任何事情。

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.keras import regularizers
from tensorflow.keras.layers import Dense,Activation,Flatten,Conv2D,MaxPooling2D,Dropout
import os
import cv2
import random
import pickle
import time
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.callbacks import TensorBoard
from google.colab import files
from tensorflow.python.framework import ops
p1=open("/content/tfds.pickle","rb")
def prepare_ds():
    dir="drive//My Drive//dataset//"
    cat=os.listdir(dir)
    i=1
    td=[]
    for x in …